The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model
Morten Jensen and
Asger Lunde ()
Econometrics Journal, 2001, vol. 4, issue 2, 10
This paper examines the capabilities of the Normal Inverse Gaussian distribu-tion as a model for stock returns. We extend the model of Barndorff-Nielsen (1997) to allow for a richer volatility structure and compare with the existing GARCH-type models. We conclude that the proposed model outperforms some of the most praised GARCH-M models. In particular, we make a big gain in modelling the skewness of equity returns.
Keywords: Normal Inverse Gaussian distribution; Observation driven model; Nonlinear state space model; Filtering. (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:4:y:2001:i:2:p:10
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